Title of article :
MODELING INSECT-EGG DATA WITH EXCESS ZEROS USING ZERO-INFLATED REGRESSION MODELS
Author/Authors :
Yesilova, Abdullah Yuzuncu Yil University - Faculty of Agriculture - Department of Animal Science, Biometry Genetic Unit, Turkey , Kaydan, M. Bora Yuzuncu Yil University - Faculty of Agriculture - Department of Plant Production, Turkey , Kaya, Yılmaz Yuzuncu Yil University, , - Vocational High School - Department of Computer Programming, Turkey
Abstract :
As zero-inflated observations occur very often in studies on plant protection, models taking into account zero-inflated observations are frequently required. Especially, zero-inflated observations occur in large numbers for insects whose post-oviposition period lasts long, or that generally lay their eggs during the first days of the oviposition period. For the data used in this study, 1114 (43.84%) of the 2541 observations were zero. In the selection of an appropriate regression model, zero-inflated negative binomial regression was chosen as the best model. In all regression models, the day of laying and the three different hosts were seen to have a significant effect on daily egg numbers (p 0.01).
Keywords :
Zero , inflated count data , Overdispersion , Zero , inflated models , Hurdle models.
Journal title :
Hacettepe Journal Of Mathematics and Statistics
Journal title :
Hacettepe Journal Of Mathematics and Statistics